Codebook example diary

knitr::opts_chunk$set(warning = FALSE, message = FALSE)
pander::panderOptions("table.split.table", Inf)

Load

library(formr)
library(dplyr)

formr_connect(email = credentials$user, password = credentials$password, host = credentials$host)
formr_results("Taeglicher_Fragebogen_1", host = credentials$host, quiet = T) -> diary

## Some items ( choice_of_clothing_2 choice_of_clothing_3 ) were negatively correlated with the total scale and 
## probably should be reversed.  
## To do this, run the function again with the 'check.keys=TRUE' option

formr_items("Taeglicher_Fragebogen_1", host = credentials$host) -> diary_items
# diary = diary %>% select(session, session_id, modified, created, ended, special_events, desirability_partner, NARQ_admiration_1, NARQ_admiration_2, NARQ_admiration_3, NARQ_rivalry_1, NARQ_rivalry_2, NARQ_rivalry_3, NARQ_admiration, NARQ_rivalry)
diary$expired = NA
rm(credentials)
knitr::opts_chunk$set(echo = FALSE)
library(ggplot2)
theme_set(theme_bw())
knitr::opts_chunk$set(error = TRUE)

codebook(diary)

Survey overview

31053 completed rows, 31097 who entered any information, 0 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame). In total, there are 31097 rows including unfinished and expired rows.

There were 1204 unique participants, of which 1202 finished filling out at least one survey.

25.83 rows per user code. A repeated survey.

if (repeated_survey) {
    overview = results %>% dplyr::group_by(session) %>% 
        dplyr::summarise(
            n = sum(!is.na(session)),
            expired = sum(!is.na(expired)),
            ended = sum(!is.na(ended))
        ) %>% 
        tidyr::gather(key, value, -session)
    if (length(unique(dplyr::filter(overview, key == "expired")$value)) == 1) {
        overview = dplyr::filter(overview, key != "expired")
    }
    print(
        ggplot2::ggplot(overview, ggplot2::aes(value, ..count..)) + ggplot2::geom_bar() + ggplot2::facet_wrap(~ key, nrow = 1)
    )
}

The first session started on 2014-03-20 17:21:28, the last session on 2016-04-16 22:23:41. People took on average 136.56 minutes (median 3.73) to answer the survey.

high_vals = sum(median(duration$duration) + 4*mad(duration$duration) < duration$duration)
ggplot2::qplot(duration$duration, binwidth = 0.5) + ggplot2::scale_x_continuous(paste("Duration (in minutes), excluding", high_vals, "values above median + 4*MAD"), limits = c(NA, median(duration$duration) + 4*mad(duration$duration)))

Scales

vars = names(results)
for (i in seq_along(vars)) {
    var = vars[i]
    cat(var,"\n", file = "~/Downloads/var.log", append = T)
    scale = results[[ var ]]
    scale_info = attributes(scale)
        if ( !is.null(scale_info)) {
        if (exists("scale", scale_info)) {
        cat(codebook_component_scale( scale, indent ))
        }
    }
}

choice_of_clothing

Reliability

psych::print.psych(scale_info$reliability)

## 
## Reliability analysis  choice_of_clothing  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean   sd
##       0.61       0.6    0.73      0.16 1.5 0.0031  3.2 0.72
## 
##  lower alpha upper     95% confidence boundaries
## 0.61 0.61 0.62 
## 
##  Reliability if an item is dropped:
##                      raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## choice_of_clothing_1      0.61      0.59    0.74      0.17 1.43   0.0032
## choice_of_clothing_2      0.72      0.72    0.77      0.27 2.59   0.0023
## choice_of_clothing_3      0.70      0.68    0.76      0.23 2.14   0.0022
## choice_of_clothing_4      0.47      0.45    0.62      0.10 0.80   0.0044
## choice_of_clothing_5      0.52      0.49    0.65      0.12 0.98   0.0040
## choice_of_clothing_6      0.51      0.49    0.66      0.12 0.95   0.0040
## choice_of_clothing_7      0.47      0.45    0.61      0.10 0.82   0.0044
## choice_of_clothing_8      0.53      0.51    0.68      0.13 1.03   0.0039
## 
##  Item statistics 
##                          n  raw.r  std.r  r.cor r.drop mean  sd
## choice_of_clothing_1 29982  0.465  0.444  0.275   0.22  3.2 1.5
## choice_of_clothing_2 29978 -0.104 -0.069 -0.260  -0.30  4.5 1.2
## choice_of_clothing_3 29973  0.093  0.113 -0.068  -0.15  3.7 1.4
## choice_of_clothing_4 29970  0.793  0.786  0.815   0.67  3.1 1.4
## choice_of_clothing_5 29971  0.691  0.687  0.665   0.54  2.1 1.3
## choice_of_clothing_6 29969  0.706  0.700  0.654   0.55  3.7 1.4
## choice_of_clothing_7 29967  0.784  0.779  0.817   0.66  2.5 1.4
## choice_of_clothing_8 29968  0.663  0.655  0.597   0.48  2.7 1.4
## 
## Non missing response frequency for each item
##                         1    2    3    4    5    6 miss
## choice_of_clothing_1 0.22 0.11 0.20 0.26 0.15 0.06 0.04
## choice_of_clothing_2 0.02 0.03 0.11 0.31 0.29 0.24 0.04
## choice_of_clothing_3 0.09 0.10 0.20 0.30 0.21 0.10 0.04
## choice_of_clothing_4 0.19 0.14 0.23 0.27 0.13 0.04 0.04
## choice_of_clothing_5 0.49 0.17 0.17 0.11 0.05 0.01 0.04
## choice_of_clothing_6 0.12 0.07 0.16 0.35 0.22 0.08 0.04
## choice_of_clothing_7 0.35 0.17 0.23 0.16 0.07 0.02 0.04
## choice_of_clothing_8 0.29 0.15 0.24 0.20 0.09 0.03 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)

likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))

type	stat	level	value
numeric	missing	.all	1130
numeric	complete	.all	29967
numeric	n	.all	31097
numeric	mean	.all	3.203
numeric	sd	.all	0.7227
numeric	min	.all	1
numeric	median	.all	3.25
numeric	quantile	25%	2.625
numeric	quantile	75%	3.75
numeric	max	.all	6
numeric	hist	▁▂▅▇▇▆▃▁▁▁	0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	choice_of_clothing_1	Seriös	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	choice_of_clothing_2	Praktisch	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	choice_of_clothing_3	Sportlich	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	choice_of_clothing_4	Sexy	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	choice_of_clothing_5	Glamourös	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	choice_of_clothing_6	Figurbetont	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	choice_of_clothing_7	Verführerisch	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	choice_of_clothing_8	Auffällig	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

NARQ_admiration

Reliability

psych::print.psych(scale_info$reliability)

## 
## Reliability analysis  NARQ_admiration  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean  sd
##       0.87      0.87    0.83      0.68 6.5 0.0014  2.6 1.3
## 
##  lower alpha upper     95% confidence boundaries
## 0.86 0.87 0.87 
## 
##  Reliability if an item is dropped:
##                   raw_alpha std.alpha G6(smc) average_r S/N alpha se
## NARQ_admiration_1      0.78      0.78    0.63      0.63 3.5   0.0025
## NARQ_admiration_2      0.75      0.75    0.60      0.60 3.0   0.0028
## NARQ_admiration_3      0.90      0.90    0.81      0.81 8.8   0.0012
## 
##  Item statistics 
##                       n raw.r std.r r.cor r.drop mean  sd
## NARQ_admiration_1 29963  0.91  0.91  0.86   0.78  2.6 1.5
## NARQ_admiration_2 29963  0.92  0.92  0.88   0.81  2.6 1.5
## NARQ_admiration_3 29963  0.84  0.84  0.68   0.65  2.6 1.5
## 
## Non missing response frequency for each item
##                      1    2    3   4    5    6 miss
## NARQ_admiration_1 0.35 0.14 0.20 0.2 0.08 0.03 0.04
## NARQ_admiration_2 0.36 0.13 0.19 0.2 0.08 0.03 0.04
## NARQ_admiration_3 0.37 0.13 0.19 0.2 0.08 0.03 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)

likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))

type	stat	level	value
numeric	missing	.all	1134
numeric	complete	.all	29963
numeric	n	.all	31097
numeric	mean	.all	2.59
numeric	sd	.all	1.316
numeric	min	.all	1
numeric	median	.all	2.667
numeric	quantile	25%	1.333
numeric	quantile	75%	3.667
numeric	max	.all	6
numeric	hist	▇▃▂▅▂▅▁▂▁▁	0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	NARQ_admiration_1	…hatte ich das Gefühl es verdient zu haben, als große Persönlichkeit angesehen zu werden.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	NARQ_admiration_2	… habe ich viel Kraft daraus gezogen, eine ganz besondere Person zu sein.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	NARQ_admiration_3	… habe ich es geschafft, mit meinen besonderen Beiträgen im Mittelpunkt zu stehen.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

NARQ_rivalry

Reliability

psych::print.psych(scale_info$reliability)

## 
## Reliability analysis  NARQ_rivalry  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean   sd
##       0.76      0.76     0.7      0.51 3.2 0.0022  1.3 0.69
## 
##  lower alpha upper     95% confidence boundaries
## 0.76 0.76 0.77 
## 
##  Reliability if an item is dropped:
##                raw_alpha std.alpha G6(smc) average_r S/N alpha se
## NARQ_rivalry_1      0.64      0.65    0.48      0.48 1.8   0.0040
## NARQ_rivalry_2      0.56      0.57    0.39      0.39 1.3   0.0049
## NARQ_rivalry_3      0.80      0.80    0.67      0.67 4.0   0.0023
## 
##  Item statistics 
##                    n raw.r std.r r.cor r.drop mean   sd
## NARQ_rivalry_1 29962  0.85  0.84  0.73   0.63  1.3 0.88
## NARQ_rivalry_2 29963  0.89  0.87  0.80   0.70  1.3 0.90
## NARQ_rivalry_3 29962  0.72  0.76  0.54   0.48  1.2 0.72
## 
## Non missing response frequency for each item
##                   1    2    3    4    5    6 miss
## NARQ_rivalry_1 0.82 0.08 0.05 0.03 0.01 0.01 0.04
## NARQ_rivalry_2 0.86 0.06 0.03 0.03 0.01 0.01 0.04
## NARQ_rivalry_3 0.87 0.06 0.03 0.02 0.01 0.00 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)

likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))

type	stat	level	value
numeric	missing	.all	1135
numeric	complete	.all	29962
numeric	n	.all	31097
numeric	mean	.all	1.296
numeric	sd	.all	0.6882
numeric	min	.all	1
numeric	median	.all	1
numeric	quantile	25%	1
numeric	quantile	75%	1
numeric	max	.all	6
numeric	hist	▇▁▁▁▁▁▁▁▁▁	0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	NARQ_rivalry_1	… habe ich genervt reagiert, wenn eine andere Frau mir die Schau gestohlen hat.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	NARQ_rivalry_2	… wollte ich, dass meine Konkurrentinnen sich blamieren oder ignoriert werden.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	NARQ_rivalry_3	… hatte ich das Gefühl, dass die meisten Frauen ziemliche Versagerinnen sind.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

male_jealousy

Reliability

psych::print.psych(scale_info$reliability)

## 
## Reliability analysis  male_jealousy  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean   sd
##       0.54      0.56    0.46       0.3 1.3 0.0043  1.3 0.64
## 
##  lower alpha upper     95% confidence boundaries
## 0.54 0.54 0.55 
## 
##  Reliability if an item is dropped:
##                 raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## male_jealousy_1      0.38      0.40    0.25      0.25 0.66   0.0066
## male_jealousy_2      0.48      0.50    0.33      0.33 1.00   0.0055
## male_jealousy_3      0.47      0.47    0.30      0.30 0.88   0.0060
## 
##  Item statistics 
##                     n raw.r std.r r.cor r.drop mean   sd
## male_jealousy_1 29962  0.78  0.75  0.54   0.40  1.4 0.96
## male_jealousy_2 29963  0.75  0.71  0.45   0.34  1.4 0.98
## male_jealousy_3 29962  0.65  0.72  0.48   0.36  1.2 0.68
## 
## Non missing response frequency for each item
##                    1    2    3    4    5    6 miss
## male_jealousy_1 0.82 0.07 0.05 0.04 0.01 0.01 0.04
## male_jealousy_2 0.83 0.06 0.04 0.04 0.01 0.01 0.04
## male_jealousy_3 0.92 0.04 0.02 0.01 0.01 0.01 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)

likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))

type	stat	level	value
numeric	missing	.all	1135
numeric	complete	.all	29962
numeric	n	.all	31097
numeric	mean	.all	1.315
numeric	sd	.all	0.6392
numeric	min	.all	1
numeric	median	.all	1
numeric	quantile	25%	1
numeric	quantile	75%	1.333
numeric	max	.all	6
numeric	hist	▇▁▁▁▁▁▁▁▁▁	0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	male_jealousy_1	… hat mich mein Partner eifersüchtig gemacht.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	male_jealousy_2	… hat mein Partner auf meinen Umgang mit anderen Männern eifersüchtig reagiert.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	male_jealousy_3	… hat mir mein Partner erzählt, er habe Komplimente von anderen Frauen erhalten.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

male_mate_retention

Reliability

psych::print.psych(scale_info$reliability)

## 
## Reliability analysis  male_mate_retention  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r  S/N    ase mean  sd
##       0.31      0.31    0.18      0.18 0.45 0.0078  3.2 1.5
## 
##  lower alpha upper     95% confidence boundaries
## 0.29 0.31 0.32 
## 
##  Reliability if an item is dropped:
##                       raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## male_mate_retention_1     0.184      0.18   0.034      0.18   NA       NA
## male_mate_retention_2     0.034      0.18      NA        NA 0.18   0.0024
## 
##  Item statistics 
##                           n raw.r std.r r.cor r.drop mean  sd
## male_mate_retention_1 29962  0.73  0.77  0.33   0.18  2.3 1.8
## male_mate_retention_2 29962  0.81  0.77  0.33   0.18  4.0 2.1
## 
## Non missing response frequency for each item
##                          1    2    3    4    5   6 miss
## male_mate_retention_1 0.59 0.06 0.07 0.12 0.07 0.1 0.04
## male_mate_retention_2 0.25 0.04 0.07 0.12 0.12 0.4 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)

likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))

type	stat	level	value
numeric	missing	.all	1135
numeric	complete	.all	29962
numeric	n	.all	31097
numeric	mean	.all	3.158
numeric	sd	.all	1.483
numeric	min	.all	1
numeric	median	.all	3.5
numeric	quantile	25%	2
numeric	quantile	75%	4
numeric	max	.all	6
numeric	hist	▇▂▃▃▇▂▂▂▁▂	0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	male_mate_retention_1	… hat mich mein Partner gefragt, mit wem ich den Tag verbracht habe.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	male_mate_retention_2	… hat mir mein Partner gesagt, dass er mich liebt.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

attention

Reliability

psych::print.psych(scale_info$reliability)

## 
## Reliability analysis  attention  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean  sd
##       0.74      0.75    0.59      0.59 2.9 0.0029  3.8 1.5
## 
##  lower alpha upper     95% confidence boundaries
## 0.74 0.74 0.75 
## 
##  Reliability if an item is dropped:
##             raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## attention_1      0.59      0.59    0.35      0.59   NA       NA
## attention_2      0.35      0.59      NA        NA 0.59   0.0044
## 
##  Item statistics 
##                 n raw.r std.r r.cor r.drop mean  sd
## attention_1 29960  0.88  0.89  0.69   0.59  4.3 1.5
## attention_2 29960  0.91  0.89  0.69   0.59  3.3 1.8
## 
## Non missing response frequency for each item
##                1    2    3    4    5    6 miss
## attention_1 0.10 0.05 0.10 0.26 0.24 0.25 0.04
## attention_2 0.26 0.11 0.17 0.18 0.14 0.14 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)

likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))

type	stat	level	value
numeric	missing	.all	1137
numeric	complete	.all	29960
numeric	n	.all	31097
numeric	mean	.all	3.756
numeric	sd	.all	1.474
numeric	min	.all	1
numeric	median	.all	4
numeric	quantile	25%	2.5
numeric	quantile	75%	5
numeric	max	.all	6
numeric	hist	▇▃▆▆▇▇▇▇▅▇	0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	attention_1	… habe ich meinem Partner gezeigt, dass er mir wichtig ist.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL
mc_button	NULL	attention_2	… habe ich meinem Partner gezeigt, dass ich mich von ihm sexuell angezogen fühle.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Single items

for (i in seq_along(vars)) {
    var = vars[i]
    cat(var,"\n", file = "~/Downloads/var.log", append = TRUE)
    item = results[[ var ]]
    item_info = attributes(item)
    if ( !is.null(item_info)) {
        if (exists("part_of_scale", item_info) || exists("scale", item_info)) {
            next
        } else if (exists("item", item_info)) {
            cat(codebook_component_single_item( item, indent ))
        } else {
            cat(codebook_component_fallback( item, var, indent))
        }
    }
}

modified

Distribution

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = item)) +
    ggplot2::stat_bin() + 
    ggplot2::ggtitle(item_name, subtitle = item_label) + 
    ggplot2::xlab("Choices")

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
POSIXct	missing	.all	0
POSIXct	complete	.all	31097
POSIXct	n	.all	31097
POSIXct	min	.all	1395332635
POSIXct	max	.all	1466869368
POSIXct	median	.all	1404748079
POSIXct	n_unique	.all	30963

Attributes

pander::pander(item_info)

• class: POSIXct and POSIXt
• tzone:
• label: user last edited survey

created

Distribution

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = item)) +
    ggplot2::stat_bin() + 
    ggplot2::ggtitle(item_name, subtitle = item_label) + 
    ggplot2::xlab("Choices")

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
POSIXct	missing	.all	0
POSIXct	complete	.all	31097
POSIXct	n	.all	31097
POSIXct	min	.all	1395332488
POSIXct	max	.all	1460838221
POSIXct	median	.all	1404747737
POSIXct	n_unique	.all	30956

Attributes

pander::pander(item_info)

• class: POSIXct and POSIXt
• tzone:
• label: user first opened survey

ended

Distribution

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = item)) +
    ggplot2::stat_bin() + 
    ggplot2::ggtitle(item_name, subtitle = item_label) + 
    ggplot2::xlab("Choices")

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
POSIXct	missing	.all	44
POSIXct	complete	.all	31053
POSIXct	n	.all	31097
POSIXct	min	.all	1395332636
POSIXct	max	.all	1466869452
POSIXct	median	.all	1404679062
POSIXct	n_unique	.all	30688

Attributes

pander::pander(item_info)

• class: POSIXct and POSIXt
• tzone:
• label: user finished survey

communication_partner_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1109
integer	complete	.all	29988
integer	n	.all	31097
integer	mean	.all	2.542
integer	sd	.all	0.5638
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	2
integer	quantile	75%	3
integer	max	.all	3
integer	hist	▁▁▁▁▆▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	communication_partner_1	Wie oft haben Sie seit Ihrem letzten Eintrag mit Ihrem Partner kommuniziert?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Gar nicht
• 2: Wenig
• 3: Viel

communication_partner_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	2171
integer	complete	.all	28926
integer	n	.all	31097
integer	mean	.all	1.92
integer	sd	.all	1.49
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	2
integer	max	.all	7
integer	hist	▇▂▁▁▂▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	communication_partner_2	Auf welche Art haben Sie hauptsächlich mit Ihrem Partner kommuniziert?	0	NULL	current(communication_partner_1) == 2 || current(communication_partner_1) == 3	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Direkter persönlicher Kontakt
• 2: Telefon
• 3: SMS
• 4: mobile Nachrichtenapp (z.B. Whatsapp)
• 5: Webcam (z.B. Skype)
• 6: Email
• 7: Chat (z.B. Facebook)

mate_retention_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1109
integer	complete	.all	29988
integer	n	.all	31097
integer	mean	.all	1.452
integer	sd	.all	0.4977
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	2
integer	max	.all	2
integer	hist	▇▁▁▁▁▁▁▁▁▆	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	mate_retention_1	Haben Sie die letzte Nacht mit Ihrem Partner verbracht?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja
• 2: nein

relationship_satisfaction_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1109
integer	complete	.all	29988
integer	n	.all	31097
integer	mean	.all	4.839
integer	sd	.all	1.208
integer	min	.all	1
integer	median	.all	5
integer	quantile	25%	4
integer	quantile	75%	6
integer	max	.all	6
integer	hist	▁▁▁▂▁▅▁▇▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	relationship_satisfaction_1	Wie zufrieden waren Sie insgesamt seit Ihrem letzten Eintrag mit Ihrer Beziehung?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Nicht zufrieden
• 2: Überwiegend nicht zufrieden
• 3: Eher nicht zufrieden
• 4: Eher zufrieden
• 5: Überwiegend zufrieden
• 6: Sehr zufrieden

mate_retention_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1109
integer	complete	.all	29988
integer	n	.all	31097
integer	mean	.all	2.441
integer	sd	.all	0.6548
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	2
integer	quantile	75%	3
integer	max	.all	3
integer	hist	▂▁▁▁▆▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	mate_retention_2	Haben Sie seit Ihrem letzten Eintrag öffentlich Intimitäten (z.B. Händchenhalten, Küssen, in den Arm nehmen) ausgetauscht?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja (1x)
• 2: ja (mehrfach)
• 3: nein

sexual_intercourse_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1109
integer	complete	.all	29988
integer	n	.all	31097
integer	mean	.all	3.108
integer	sd	.all	1.218
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	2
integer	quantile	75%	4
integer	max	.all	5
integer	hist	▃▁▅▁▇▁▁▆▁▃	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	sexual_intercourse_1	Wie sehr hatten Sie seit Ihrem letzten Eintrag Lust, mit Ihrem Partner Geschlechtsverkehr zu haben?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: gar nicht
• 2: kaum
• 3: etwas
• 4: viel
• 5: sehr viel

sexual_intercourse_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1109
integer	complete	.all	29988
integer	n	.all	31097
integer	mean	.all	2.632
integer	sd	.all	0.7301
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	3
integer	quantile	75%	3
integer	max	.all	3
integer	hist	▂▁▁▁▁▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	sexual_intercourse_2	Hatten Sie seit Ihrem letzten Eintrag mit Ihrem Partner Geschlechtsverkehr?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja (1x)
• 2: ja (mehrfach)
• 3: nein

sexual_intercourse_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	24561
integer	complete	.all	6536
integer	n	.all	31097
integer	mean	.all	1.603
integer	sd	.all	0.4892
integer	min	.all	1
integer	median	.all	2
integer	quantile	25%	1
integer	quantile	75%	2
integer	max	.all	2
integer	hist	▅▁▁▁▁▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	sexual_intercourse_3	Wer hat den Geschlechtsverkehr stärker initiiert?	0	NULL	current(sexual_intercourse_2) == 1 || current(sexual_intercourse_2) == 2	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ich
• 2: mein Partner

sexual_intercourse_4

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	24562
integer	complete	.all	6535
integer	n	.all	31097
integer	mean	.all	5.136
integer	sd	.all	0.9874
integer	min	.all	1
integer	median	.all	5
integer	quantile	25%	5
integer	quantile	75%	6
integer	max	.all	6
integer	hist	▁▁▁▁▁▃▁▆▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	sexual_intercourse_4	Wie zufrieden waren Sie mit dem Geschlechtsverkehr?	0	NULL	current(sexual_intercourse_2) == 1 || current(sexual_intercourse_2) == 2	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Nicht zufrieden
• 2: Überwiegend nicht zufrieden
• 3: Eher nicht zufrieden
• 4: Eher zufrieden
• 5: Überwiegend zufrieden
• 6: Sehr zufrieden

sexual_intercourse_5

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1110
integer	complete	.all	29987
integer	n	.all	31097
integer	mean	.all	2.684
integer	sd	.all	0.6787
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	3
integer	quantile	75%	3
integer	max	.all	3
integer	hist	▁▁▁▁▁▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	sexual_intercourse_5	Hatten Sie seit Ihrem letzten Eintrag anderen sexuellen Kontakt mit Ihrem Partner (Oralverkehr, Petting etc.)?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja (1x)
• 2: ja (mehrfach)
• 3: nein

extra_pair_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1110
integer	complete	.all	29987
integer	n	.all	31097
integer	mean	.all	1.986
integer	sd	.all	0.1159
integer	min	.all	1
integer	median	.all	2
integer	quantile	25%	2
integer	quantile	75%	2
integer	max	.all	2
integer	hist	▁▁▁▁▁▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	extra_pair_1	Hatten Sie seit Ihrem letzten Eintrag intimen Kontakt mit einer anderen Person als Ihrem Partner?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja
• 2: nein

extra_pair_1b

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	30690
integer	complete	.all	407
integer	n	.all	31097
integer	mean	.all	1.661
integer	sd	.all	0.474
integer	min	.all	1
integer	median	.all	2
integer	quantile	25%	1
integer	quantile	75%	2
integer	max	.all	2
integer	hist	▅▁▁▁▁▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	extra_pair_1b	Hatten Sie seit Ihrem letzten Eintrag Sex mit einer anderen Person als Ihrem Partner?	0	NULL	current(extra_pair_1) == 1	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja
• 2: nein

menstruation_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1110
integer	complete	.all	29987
integer	n	.all	31097
integer	mean	.all	1.839
integer	sd	.all	0.3673
integer	min	.all	1
integer	median	.all	2
integer	quantile	25%	2
integer	quantile	75%	2
integer	max	.all	2
integer	hist	▂▁▁▁▁▁▁▁▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	menstruation_1	Hatten Sie seit Ihrem letzten Eintrag menstruelle Blutungen (Ihre Periode)?	0	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja
• 2: nein

menstruation_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	26288
integer	complete	.all	4809
integer	n	.all	31097
integer	mean	.all	3.43
integer	sd	.all	1.682
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	2
integer	quantile	75%	5
integer	max	.all	6
integer	hist	▇▇▁▇▁▇▁▇▁▆	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc	NULL	menstruation_2	War heute der erste Tag Ihrer menstruellen Blutung (Periode)?	0	mc_vertical	current(menstruation_1) == 1	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: ja
• 2: nein (gestern)
• 3: nein (vorgestern)
• 4: nein (vor 3 Tagen)
• 5: nein (vor 4 Tagen)
• 6: nein (Beginn liegt noch länger zurück)

menstruation_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	26288
integer	complete	.all	4809
integer	n	.all	31097
integer	mean	.all	1.572
integer	sd	.all	0.717
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	2
integer	max	.all	3
integer	hist	▇▁▁▁▅▁▁▁▁▂	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	menstruation_3	Wie stark ist Ihre menstruelle Blutung (Periode) heute?	0	NULL	current(menstruation_1) == 1	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1:
• 2:
• 3:

self_esteem_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1130
integer	complete	.all	29967
integer	n	.all	31097
integer	mean	.all	4.276
integer	sd	.all	1.19
integer	min	.all	1
integer	median	.all	4
integer	quantile	25%	4
integer	quantile	75%	5
integer	max	.all	6
integer	hist	▁▁▁▃▁▇▁▇▁▃	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	self_esteem_1	… war ich im Großen und Ganzen zufrieden mit mir selbst.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

desirability_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1130
integer	complete	.all	29967
integer	n	.all	31097
integer	mean	.all	3.676
integer	sd	.all	1.413
integer	min	.all	1
integer	median	.all	4
integer	quantile	25%	3
integer	quantile	75%	5
integer	max	.all	6
integer	hist	▃▂▁▅▁▇▁▅▁▂	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	desirability_1	… habe ich mich sexuell begehrenswert gefühlt.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

desirability_partner

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1132
integer	complete	.all	29965
integer	n	.all	31097
integer	mean	.all	3.818
integer	sd	.all	1.453
integer	min	.all	1
integer	median	.all	4
integer	quantile	25%	3
integer	quantile	75%	5
integer	max	.all	6
integer	hist	▃▂▁▅▁▇▁▆▁▃	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	desirability_partner	…fand ich meinen Partner besonders sexuell anziehend.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

jealousy_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1134
integer	complete	.all	29963
integer	n	.all	31097
integer	mean	.all	2.406
integer	sd	.all	1.825
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	4
integer	max	.all	6
integer	hist	▇▁▁▁▁▂▁▁▁▂	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	jealousy_1	… habe ich meinen Partner gefragt, mit wem er den Tag verbracht hat.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

mate_retention_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1135
integer	complete	.all	29962
integer	n	.all	31097
integer	mean	.all	2.869
integer	sd	.all	1.703
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	1
integer	quantile	75%	4
integer	max	.all	6
integer	hist	▇▂▁▃▁▅▁▃▁▂	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	mate_retention_3	… habe ich mich für meinen Partner besonders hübsch gemacht.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

mate_retention_4

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1135
integer	complete	.all	29962
integer	n	.all	31097
integer	mean	.all	3.991
integer	sd	.all	2.054
integer	min	.all	1
integer	median	.all	5
integer	quantile	25%	1
integer	quantile	75%	6
integer	max	.all	6
integer	hist	▅▁▁▂▁▂▁▂▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	mate_retention_4	… habe ich meinem Partner gesagt, dass ich ihn liebe.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

mate_retention_5

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1135
integer	complete	.all	29962
integer	n	.all	31097
integer	mean	.all	1.623
integer	sd	.all	1.227
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	2
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	mate_retention_5	… habe ich vor meinem Partner über andere Frauen gelästert.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

mate_retention_6

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1136
integer	complete	.all	29961
integer	n	.all	31097
integer	mean	.all	2.784
integer	sd	.all	1.568
integer	min	.all	1
integer	median	.all	3
integer	quantile	25%	1
integer	quantile	75%	4
integer	max	.all	6
integer	hist	▇▃▁▅▁▅▁▂▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	mate_retention_6	… war ich in Bezug auf meinen Partner sehr anhänglich.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

male_attention_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1137
integer	complete	.all	29960
integer	n	.all	31097
integer	mean	.all	3.541
integer	sd	.all	1.842
integer	min	.all	1
integer	median	.all	4
integer	quantile	25%	2
integer	quantile	75%	5
integer	max	.all	6
integer	hist	▇▃▁▅▁▆▁▆▁▇	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	male_attention_1	… hat mir mein Partner gezeigt, dass er sich von mir sexuell angezogen fühlt.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1137
integer	complete	.all	29960
integer	n	.all	31097
integer	mean	.all	2.604
integer	sd	.all	1.608
integer	min	.all	1
integer	median	.all	2
integer	quantile	25%	1
integer	quantile	75%	4
integer	max	.all	6
integer	hist	▇▂▁▃▁▃▁▂▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_2	…war es mir wichtig, dass mich andere Männer als attraktiv wahrnehmen.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.954
integer	sd	.all	1.514
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	3
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_3	… habe ich Komplimente von anderen Männern erhalten.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_4

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.295
integer	sd	.all	0.9242
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	1
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_4	… habe ich via Medien mit Freunden, Bekannten oder Kollegen geflirtet.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_5

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.94
integer	sd	.all	1.719
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	2
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_5	… bin ich ohne meinen Partner ausgegangen.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_6

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	2.254
integer	sd	.all	1.843
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	4
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▂	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_6	… bin ich ohne meinen Partner an einen Ort gegangen, wo man Männer treffen kann.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_7

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.595
integer	sd	.all	1.241
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	1
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_7	… habe ich mir Gedanken über einen anderen potentiellen Partner gemacht.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_8

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.248
integer	sd	.all	0.8024
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	1
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_8	… habe ich mit Männern geflirtet, die ich nicht kannte.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_9

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.39
integer	sd	.all	1.053
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	1
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_9	… habe ich mit Freunden, Kollegen oder Bekannten geflirtet.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_10

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.518
integer	sd	.all	1.216
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	1
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_10	… habe ich mich zu einem Freund, Bekannten oder Kollegen hingezogen gefühlt	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_11

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.237
integer	sd	.all	0.801
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	1
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_11	… habe ich mich zu einem Mann hingezogen gefühlt, den ich nicht kannte.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_12

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	2.248
integer	sd	.all	1.629
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	4
integer	max	.all	6
integer	hist	▇▁▁▁▁▂▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_12	… sind mir attraktive Männer in meiner Umgebung aufgefallen.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

extra_pair_13

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
integer	missing	.all	1138
integer	complete	.all	29959
integer	n	.all	31097
integer	mean	.all	1.481
integer	sd	.all	1.2
integer	min	.all	1
integer	median	.all	1
integer	quantile	25%	1
integer	quantile	75%	1
integer	max	.all	6
integer	hist	▇▁▁▁▁▁▁▁▁▁	0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
mc_button	NULL	extra_pair_13	… hatte ich sexuelle Fantasien mit anderen Männern als meinem Partner.	0	mc-width100 show_value_instead_of_label	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

• 1: Stimme nicht zu
• 2: Stimme überwiegend nicht zu
• 3: Stimme eher nicht zu
• 4: Stimme eher zu
• 5: Stimme überwiegend zu
• 6: Stimme voll zu

special_events

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)

if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

## More than  2012  unique values, so not shown.

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))

type	stat	level	value
character	missing	.all	28229
character	complete	.all	2868
character	n	.all	31097
character	min	.all	1
character	max	.all	2077
character	empty	.all	0
character	n_unique	.all	2011

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))

type	type_options	name	label	optional	class	showif	value	order
textarea	NULL	special_events	Gab es seit Ihrem letzten Eintrag besondere nennenswerte Ereignisse hinsichtlich Ihres Beziehungslebens?	1	NULL	NULL	NULL	NULL

Choices

if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

Missingness report

There were 31053 rows completed, 31097 who entered any information, 0 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame).

Missingness finishers

among those who finished the survey

missingness = missingness_patterns(
    dplyr::select(dplyr::filter(results, !is.na(ended)), -expired, -ended) )

##  index                         col missings
##      1               extra_pair_1b    30646
##      2              special_events    28185
##      3              menstruation_2    26244
##      4              menstruation_3    26244
##      5        sexual_intercourse_4    24518
##      6        sexual_intercourse_3    24517
##      7     communication_partner_2     2127
##      8                extra_pair_3     1094
##      9                extra_pair_4     1094
##     10                extra_pair_5     1094
##     11                extra_pair_6     1094
##     12                extra_pair_7     1094
##     13                extra_pair_8     1094
##     14                extra_pair_9     1094
##     15               extra_pair_10     1094
##     16               extra_pair_11     1094
##     17               extra_pair_12     1094
##     18               extra_pair_13     1094
##     19                 attention_1     1093
##     20                 attention_2     1093
##     21            male_attention_1     1093
##     22                extra_pair_2     1093
##     23                   attention     1093
##     24            mate_retention_6     1092
##     25              NARQ_rivalry_1     1091
##     26              NARQ_rivalry_3     1091
##     27             male_jealousy_1     1091
##     28             male_jealousy_3     1091
##     29       male_mate_retention_1     1091
##     30       male_mate_retention_2     1091
##     31            mate_retention_3     1091
##     32            mate_retention_4     1091
##     33            mate_retention_5     1091
##     34                NARQ_rivalry     1091
##     35               male_jealousy     1091
##     36         male_mate_retention     1091
##     37           NARQ_admiration_1     1090
##     38           NARQ_admiration_2     1090
##     39           NARQ_admiration_3     1090
##     40              NARQ_rivalry_2     1090
##     41                  jealousy_1     1090
##     42             male_jealousy_2     1090
##     43             NARQ_admiration     1090
##     44        desirability_partner     1088
##     45        choice_of_clothing_7     1086
##     46               self_esteem_1     1086
##     47              desirability_1     1086
##     48          choice_of_clothing     1086
##     49        choice_of_clothing_8     1085
##     50        choice_of_clothing_6     1084
##     51        choice_of_clothing_4     1083
##     52        choice_of_clothing_5     1082
##     53        choice_of_clothing_3     1080
##     54        choice_of_clothing_2     1075
##     55        choice_of_clothing_1     1071
##     56        sexual_intercourse_5     1066
##     57                extra_pair_1     1066
##     58              menstruation_1     1066
##     59     communication_partner_1     1065
##     60            mate_retention_1     1065
##     61 relationship_satisfaction_1     1065
##     62            mate_retention_2     1065
##     63        sexual_intercourse_1     1065
##     64        sexual_intercourse_2     1065

pander::pander(missingness)

Pattern	Freq	Culprit
1_2_3_4_5_6___________________________________________________________________________________________________________________________________________________________________________	16372
1_2_3_4_______________________________________________________________________________________________________________________________________________________________________________	5407
1_2_____5_6___________________________________________________________________________________________________________________________________________________________________________	3581
1_3_4_5_6_________________________________________________________________________________________________________________________________________________________________________	1742
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_60_61_62_63_64	1065
1_2_3_4_5_6_7_________________________________________________________________________________________________________________________________________________________________________	726
1_2___________________________________________________________________________________________________________________________________________________________________________________	523
1_3_4_____________________________________________________________________________________________________________________________________________________________________________	444
1_______5_6___________________________________________________________________________________________________________________________________________________________________________	407
2_3_4_5_6_________________________________________________________________________________________________________________________________________________________________________	215
1_2_____5_6_7_________________________________________________________________________________________________________________________________________________________________________	119
1_3_4_5_6_7_______________________________________________________________________________________________________________________________________________________________________	116
1_____________________________________________________________________________________________________________________________________________________________________________________	71	extra_pair_1b
25_6________________________________________________________________________________________________________________________________________________________________________	42
____3_4_5_6___________________________________________________________________________________________________________________________________________________________________________	37
2_3_4_____________________________________________________________________________________________________________________________________________________________________________	33
2_3_4_5_6_7_______________________________________________________________________________________________________________________________________________________________________	27
1_______5_6_7_________________________________________________________________________________________________________________________________________________________________________	26
1_2_3_4_____7_________________________________________________________________________________________________________________________________________________________________________	12
2_________________________________________________________________________________________________________________________________________________________________________________	10	special_events
____3_4_______________________________________________________________________________________________________________________________________________________________________________	10
25_6_7______________________________________________________________________________________________________________________________________________________________________	8
2_______7_________________________________________________________________________________________________________________________________________________________________________	7
____3_4_5_6_7_________________________________________________________________________________________________________________________________________________________________________	5
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54____________________________	4
2_3_47______________________________________________________________________________________________________________________________________________________________________	4
________5_6___________________________________________________________________________________________________________________________________________________________________________	4
1_2_________7_________________________________________________________________________________________________________________________________________________________________________	3
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44__________________________________________________________	2
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_____________________________________________________________	2
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_________________________________	2
1_2_____5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_________________________	2
________5_6_7_________________________________________________________________________________________________________________________________________________________________________	2
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55___________________________	1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_55________________________	1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_________________________________	1
1_2_3_4_5_6_7__________________________________________________25_26______________________34_______________________________45_______48_______51_______________________________________	1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_______________________________	1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50________________________________________	1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49___________________________________________	1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_4446_47_________________________________________________	1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_4143_44_45_46_47_48_49_50_51_52_53_54_55_________________________	1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_____27_28_29_30_31_32_33_35_36_____________42__________________________________________________________________	1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_________________________________________________________________________________________________________________________	1
1_2_3_4_5_____________________________________________________________________________________________________________________________________________________________________________	1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58__________________	1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54______________________________	1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52____________________________________	1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24________________________________________________________________________________________________________________________	1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18__________________________________________________________________________________________________________________________________________	1
1_2_____5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52__________________________________	1
1_2_____5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50________________________________________	1
1_3_47______________________________________________________________________________________________________________________________________________________________________	1
____3_4_____7_________________________________________________________________________________________________________________________________________________________________________	1
____________7_________________________________________________________________________________________________________________________________________________________________________	1	communication_partner_2
______________________________________________________________________________________________________________________________________________________________________________________	1	_

Missingness starters

among those who started the survey

missingness = missingness_patterns(
    dplyr::filter(results, !is.na(modified)) )

##  index                         col missings
##      1                     expired    31097
##      2               extra_pair_1b    30690
##      3              special_events    28229
##      4              menstruation_2    26288
##      5              menstruation_3    26288
##      6        sexual_intercourse_4    24562
##      7        sexual_intercourse_3    24561
##      8     communication_partner_2     2171
##      9                extra_pair_3     1138
##     10                extra_pair_4     1138
##     11                extra_pair_5     1138
##     12                extra_pair_6     1138
##     13                extra_pair_7     1138
##     14                extra_pair_8     1138
##     15                extra_pair_9     1138
##     16               extra_pair_10     1138
##     17               extra_pair_11     1138
##     18               extra_pair_12     1138
##     19               extra_pair_13     1138
##     20                 attention_1     1137
##     21                 attention_2     1137
##     22            male_attention_1     1137
##     23                extra_pair_2     1137
##     24                   attention     1137
##     25            mate_retention_6     1136
##     26              NARQ_rivalry_1     1135
##     27              NARQ_rivalry_3     1135
##     28             male_jealousy_1     1135
##     29             male_jealousy_3     1135
##     30       male_mate_retention_1     1135
##     31       male_mate_retention_2     1135
##     32            mate_retention_3     1135
##     33            mate_retention_4     1135
##     34            mate_retention_5     1135
##     35                NARQ_rivalry     1135
##     36               male_jealousy     1135
##     37         male_mate_retention     1135
##     38           NARQ_admiration_1     1134
##     39           NARQ_admiration_2     1134
##     40           NARQ_admiration_3     1134
##     41              NARQ_rivalry_2     1134
##     42                  jealousy_1     1134
##     43             male_jealousy_2     1134
##     44             NARQ_admiration     1134
##     45        desirability_partner     1132
##     46        choice_of_clothing_7     1130
##     47               self_esteem_1     1130
##     48              desirability_1     1130
##     49          choice_of_clothing     1130
##     50        choice_of_clothing_8     1129
##     51        choice_of_clothing_6     1128
##     52        choice_of_clothing_4     1127
##     53        choice_of_clothing_5     1126
##     54        choice_of_clothing_3     1124
##     55        choice_of_clothing_2     1119
##     56        choice_of_clothing_1     1115
##     57        sexual_intercourse_5     1110
##     58                extra_pair_1     1110
##     59              menstruation_1     1110
##     60     communication_partner_1     1109
##     61            mate_retention_1     1109
##     62 relationship_satisfaction_1     1109
##     63            mate_retention_2     1109
##     64        sexual_intercourse_1     1109
##     65        sexual_intercourse_2     1109
##     66                       ended       44

pander::pander(missingness)

Pattern	Freq	Culprit
1_2_3_4_5_6_7_______________________________________________________________________________________________________________________________________________________________________________	16372
1_2_3_4_5___________________________________________________________________________________________________________________________________________________________________________________	5407
1_2_3_____6_7_______________________________________________________________________________________________________________________________________________________________________________	3581
1_2_4_5_6_7_____________________________________________________________________________________________________________________________________________________________________________	1742
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_60_61_62_63_64_65___	1065
1_2_3_4_5_6_7_8_____________________________________________________________________________________________________________________________________________________________________________	726
1_2_3_______________________________________________________________________________________________________________________________________________________________________________________	523
1_2_4_5_________________________________________________________________________________________________________________________________________________________________________________	444
1_2_______6_7_______________________________________________________________________________________________________________________________________________________________________________	407
1_3_4_5_6_7_____________________________________________________________________________________________________________________________________________________________________________	215
1_2_3_____6_7_8_____________________________________________________________________________________________________________________________________________________________________________	119
1_2_4_5_6_7_8___________________________________________________________________________________________________________________________________________________________________________	116
1_2_________________________________________________________________________________________________________________________________________________________________________________________	71
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_60_61_62_63_64_65_66	44
1_36_7____________________________________________________________________________________________________________________________________________________________________________	42
1_____4_5_6_7_______________________________________________________________________________________________________________________________________________________________________________	37
1_3_4_5_________________________________________________________________________________________________________________________________________________________________________________	33
1_3_4_5_6_7_8___________________________________________________________________________________________________________________________________________________________________________	27
1_2_______6_7_8_____________________________________________________________________________________________________________________________________________________________________________	26
1_2_3_4_5_____8_____________________________________________________________________________________________________________________________________________________________________________	12
1_3_____________________________________________________________________________________________________________________________________________________________________________________	10
1_____4_5___________________________________________________________________________________________________________________________________________________________________________________	10
1_36_7_8__________________________________________________________________________________________________________________________________________________________________________	8
1_3_______8_____________________________________________________________________________________________________________________________________________________________________________	7
1_____4_5_6_7_8_____________________________________________________________________________________________________________________________________________________________________________	5
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_______________________________	4
1_3_4_58__________________________________________________________________________________________________________________________________________________________________________	4
1_________6_7_______________________________________________________________________________________________________________________________________________________________________________	4
1_2_3_________8_____________________________________________________________________________________________________________________________________________________________________________	3
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_____________________________________________________________	2
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44________________________________________________________________	2
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54____________________________________	2
1_2_3_____6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56____________________________	2
1_________6_7_8_____________________________________________________________________________________________________________________________________________________________________________	2
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56______________________________	1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_56___________________________	1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54____________________________________	1
1_2_3_4_5_6_7_8___________________________________________________26_27______________________35_______________________________46_______49_______52__________________________________________	1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54__________________________________	1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51___________________________________________	1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50______________________________________________	1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_4547_48____________________________________________________	1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_4244_45_46_47_48_49_50_51_52_53_54_55_56____________________________	1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_____28_29_30_31_32_33_34_36_37_____________43_____________________________________________________________________	1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24____________________________________________________________________________________________________________________________	1
1_2_3_4_5_6_________________________________________________________________________________________________________________________________________________________________________________	1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_____________________	1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_________________________________	1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_______________________________________	1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25___________________________________________________________________________________________________________________________	1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_____________________________________________________________________________________________________________________________________________	1
1_2_3_____6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_____________________________________	1
1_2_3_____6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51___________________________________________	1
1_2_4_58__________________________________________________________________________________________________________________________________________________________________________	1
1_____4_5_____8_____________________________________________________________________________________________________________________________________________________________________________	1
1_____________8_____________________________________________________________________________________________________________________________________________________________________________	1
1___________________________________________________________________________________________________________________________________________________________________________________________	1	expired

Items

DT::datatable(dplyr::select(as.data.frame(diary_items), -choice_list, -id, -study_id, -index), rownames = FALSE, filter = "top", extensions = 'Buttons', options = list(
    dom = 'Bfrtip',
    buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
    pageLength = 200
  ))